Methods and Apparatus for Quantitative Flow Analysis

Abstract

Method for quantitative flow analysis of a tree of conduits perfusing an organ from at least two bi-dimensional images, the method comprising the following steps: a) making a 3D reconstruction of at least part of the tree from said at least two bi-dimensional images; b) identifying a segment of interest within the 3D reconstruction either automatically or semi-automatically upon user input; c) making calculations based on the 3D reconstruction to determine geometrical features of the conduits such as diameters, lengths, curvatures, centrelines or the like; d) receiving indication from the user to input a multi-scale functional model of the tree to be considered for the flow analysis and to input the location of the segment of interest within such model; e) adjusting the part of the functional model related to the segment of interest using geometrical features of the 3D reconstruction; f) performing quantitative flow analysis based on the functional model so obtained. A corresponding apparatus and computer program are also disclosed.

Description

FIELD OF THE INVENTION[0001]The present application relates to the technical field of medical imaging, particularly angiography imaging, although it can find application in any field where there is the need to quantify flow in obstructed or partially obstructed conduits such as in non destructive testing applications.STATE OF THE ART[0002]Cardiovascular disease (CVD) is one of the leading causes of deaths worldwide. CVD generally refers to conditions that involve narrowed or blocked blood vessels that can lead to reduced or absent blood and therefore oxygen supply to the sections distal to the stenosis, resulting in, for instance, chest pain (angina) and ischemia. A very important aspect in the prevention and treatment of CVD is the functional assessment of such narrowed or blocked blood vessels.[0003]At the moment X-ray angiography is the standard technique for anatomical assessment of the coronary arteries and the diagnosis of coronary artery disease. During X-ray angiography seve...

AI Technical Summary

Benefits of technology

The patent text describes a method for measuring the flow of a fluid, specifically the coronary blood flow, using images taken during inter-operative procedures. The method corrects the functional model to account for the status of the conduits forming the tree using quantitative image analysis. This analysis can be based on densitometric image analysis and geometric information. The method is quick to perform and requires less imaging-related load on the patient. A computer product and an X-ray angiography apparatus are also described for performing the method. The technical effects of the patent text include improved accuracy and precision in measuring flow and the ability to measure flow even in real-time.

Problems solved by technology

CVD generally refers to conditions that involve narrowed or blocked blood vessels that can lead to reduced or absent blood and therefore oxygen supply to the sections distal to the stenosis, resulting in, for instance, chest pain (angina) and ischemia.

Although objectivity, reproducibility and accuracy in assessment of lesion severity has improved by means of quantitative coronary analysis tools, the functional significance of atherosclerotic lesions, which is the most important prognostic factor in patients with coronary artery disease, cannot be appreciated by conventional angiography which quantifies the obstruction severity based on extracted geometric features.

Underestimation of the stenosis, however, could induce risks because the patient is left untreated when the stenosis is in reality severe.

The technique is associated with the additional cost of a pressure wire which can be only be used once.

Furthermore, measuring FFR requires invasive catheterisation with the associated cost and procedure time.

Also, in order to induce (maximum) hyperemia, additional drug infusion (adenosine or papaverine) is required, which is an extra burden for the patient.

One of the most difficult aspects of vFFR is the coupling of the different aspects of the computations (anatomical as well as functional) without having high computational complexity, but still incorporating as much patient specific information as needed for accurate computations.

One of the largest challenges is to apply realistic boundary conditions in order to simulate dynamic blood flow in the extracted geometry of the imaged vascular system.

Disadvantages of these approaches are that all calculations are performed exclusively in 3D.

This results in a method that is of high computational complexity.

Furthermore, due to the fact that these methods required MR or CT imaging, they cannot be used during the intervention in which x-ray angiography is the standard imaging modality.

However some underlying assumptions of these methods provide limitations as described by Wijngaard et al ‘3D imaging of vascular networks for biophysical modeling of perfusion distribution within the heart’, Journal of Biomechanics 46 (2013) 229-239.

However, due to their size these collateral vessels are not commonly visible on X-ray angiography images and further steps are needed to determine the presence of the collateral flow based on X-ray angiography.

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